Skip to main content

Theory and Methods in the Study of Distributive Politics*


While many scholars have moved toward using individual-level data to test theories of distributive politics, no studies have ever explicitly examined differences between individual and aggregate analyses of a distributive program. By leveraging nationwide individual-level data on both revealed voter preferences and the actual receipt of particularistic benefits through a contemporary Venezuelan land reform initiative, this article demonstrates that scholars can most effectively test and refine individual-level theories of distributive politics by combining both individual- and macro-level data. There are at least two advantages to doing so. First, comparing and contrasting findings from data at different levels of analysis can enable researchers to paint a more complete picture of distributive targeting. Second, when distributive benefits can be impacted or redirected by subnational politicians, as is common with many distributive programs, individual-level data alone can generate mistaken inferences that are an artifact of competing targeting attempts at different levels of government instead of initial targeting strategies. I demonstrate both of these points and discuss practical and simple recommendations regarding data collection strategies for the purposes of effectively testing theories of distributive politics.

Hide All

Michael Albertus, Assistant Professor of Political Science, Department of Political Science, University of Chicago, 5828 Pick Hall, Chicago, IL 60637 ( To view supplementary material for this article, please visit

Hide All
Albertus Michael. 2013. ‘Vote buying with multiple distributive goods’. Comparative Political Studies 46(9):10821111.
Albertus Michael. 2015. ‘The Role of Subnational Politicians in Distributive Politics: Political Bias in Venezuela’s Land Reform Under Chávez’. Comparative Political Studies 48(13):16671710.
Ansolabehere Stephen, and Snyder James. 2006. ‘Party Control of State Government and the Distribution of Public Expenditures’. Scandinavian Journal of Economics 108(4):547569.
Arulampalam Wiji, Dasgupta Sugato, Dhillon Amrita, and Dutta Bhaskar. 2009. ‘Electoral goals and center-state transfers’. Journal of Development Economics 88(1):103119.
Calvo Ernesto, and Victoria Murillo Maria. 2004. ‘Who delivers? Partisan clients in the Argentine electoral market’. American Journal of Political Science 48(4):742757.
Carlin Ryan, and Moseley Mason. 2015. ‘Good Democrats, Bad Targets: Democratic Values and Clientelistic Vote Buying’. Journal of Politics 77(1):1426.
Cox Gary. 2009. ‘Swing Voters, Core Voters and Distributive Politics’. In Ian Shapiro (ed.), Political Representation, pp. 342357. Cambridge, UK: Cambridge University Press.
Cox Gary, and McCubbins Mathew. 1986. ‘Electoral Politics as a Redistributive Game’. Journal of Politics 48(2):370389.
Dixit Avinash, and Londregan John. 1996. ‘The Determinants of the Success of Special Interests in Redistributive Politics’. Journal of Politics 58:11321155.
Gonzalez-Ocantos Ezequiel, Carlos Meléndez Chad Kiewiet de Jonge, Osorio Javier, and Nickerson David. 2012. ‘Vote Buying and Social Desirability Bias: Experimental Evidence from Nicaragua’. American Journal of Political Science 56(1):202217.
Hawkins Kirk, and Hansen David. 2006. ‘Dependent Civil Society: The Círculos Bolivarianos in Venezuela’. Latin American Research Review 41(1):102132.
Lander Luis, and López Maya Margarita. 2005. ‘Referendo Revocatorio Elecciones Regionales en Venezuela’. Revista Venezolana de Economía y Ciencias Sociales 11:4358.
Lawson Chappell, and Greene Kenneth. 2014. ‘Making Clientelism Work: How Norms of Reciprocity Increase Voter Compliance’. Comparative Politics 47(1):6185.
Levitt Steven, and Snyder James. 1995. ‘Political Parties and the Distribution of Federal Outlays’. American Journal of Political Science 39(4):958980.
Lindbeck Assar, and Weibull Jorgen. 1987. ‘Balanced Budget Redistribution and the Outcome of Political Competition’. Public Choice 52:273297.
Nichter Simeon. 2008. ‘Vote Buying or Turnout Buying? Machine Politics and the Secret Ballot’. American Political Science Review 102(1):1931.
Penfold Michael. 2007. ‘Clientelism and Social Funds: Evidence from Chávez’s Misiones’. Latin American Politics and Society 49(4):6984.
Schady Norbert R. 2000. ‘The Political Economy of Expenditures by the Peruvian Social Fund (FONCODES), 1991–95’. American Political Science Review 94(2):289304.
Solé-Ollé Albert, and Sorribas-Navarro Pilar. 2008. ‘The Effects of Partisan Alignment on the Allocation of Intergovernmental Transfers’. Journal of Public Economics 92(12):23022319.
Stokes Susan. 2005. ‘Perverse Accountability: A Formal Model of Machine Politics With Evidence From Argentina’. American Political Science Review 99:315325.
Stokes Susan, Dunning Thad, Nazareno Marcelo, and Brusco Valeria. 2013. Brokers, Voters, and Clientelism. New York, NY: Cambridge University Press.
Szwarcberg Mariela. 2012. ‘Why Parties Conduct Rallies in Argentina’. Comparative Politics 45(1):88106.
Ward Hugh, and John Peter. 1999. ‘Targeting Benefits for Electoral Gain’. Political Studies 47(1):3252.
Weitz-Shapiro Rebecca. 2014. Curbing Clientelism in Argentina. New York: Cambridge University Press.
Zaragaza Rodrigo. 2016. ‘Party Machines and Voter-Customized Rewards Strategies’. Journal of Theoretical Politics 28(4):678701.
Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

Political Science Research and Methods
  • ISSN: 2049-8470
  • EISSN: 2049-8489
  • URL: /core/journals/political-science-research-and-methods
Please enter your name
Please enter a valid email address
Who would you like to send this to? *
Type Description Title
Supplementary materials

Albertus supplementary material
Albertus supplementary material 1

 PDF (643 KB)
643 KB
Supplementary materials

Albertus Dataset



Altmetric attention score

Full text views

Total number of HTML views: 4
Total number of PDF views: 59 *
Loading metrics...

Abstract views

Total abstract views: 512 *
Loading metrics...

* Views captured on Cambridge Core between 14th August 2017 - 20th January 2018. This data will be updated every 24 hours.